A novel Gaussian approximation based mixture reduction algorithm is proposed for semi-blind joint channel tracking and symbol detection for spatial multiplexing multiple-input multiple-output (MIMO) systems with frequency-flat time-selective channels. The proposed algorithm is based on a modified sequential Gaussian approximation detector (SGA) which takes into account channel uncertainty, and the first order generalized pseudo-Bayesian (GPB1) channel estimator. Simulation results show that the proposed algorithm performs better than the conventional and computationally expensive decision-directed method with Kalman filter based channel estimation and a posteriori probability (APP) symbol detection.
|Translated title of the contribution||Gaussian approximation based mixture reduction for joint channel estimation and detection in MIMO systems|
|Pages (from-to)||2384 - 2389|
|Number of pages||6|
|Journal||IEEE Transactions on Wireless Communications|
|Publication status||Published - Jul 2007|
Bibliographical notePublisher: Institute of Electrical and Electronics Engineers (IEEE)
Rose publication type: Journal article
Sponsorship: This work was supported by Toshiba Research Europe Ltd (Bristol), UK.
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- joint estimation and detection
- MIMO systems
- multiple model estimation
- multiuser detection
- time-varying channels